TransFAIR study: a European multicentre experimental comparison of EHR2EDC technology to the usual manual method for eCRF data collection

Purpose Regulatory authorities including the Food and Drug Administration and the European Medicines Agency are encouraging to conduct clinical trials using routinely collected data. The aim of the TransFAIR experimental comparison was to evaluate, within real-life conditions, the ability of the Electronic Health Records to Electronic Data Capture (EHR2EDC) module to accurately transfer from EHRs to EDC systems patients’ data of clinical studies in various therapeutic areas. Methods A prospective study including six clinical trials from three different sponsors running in three hospitals across Europe has been conducted. The same data from the six studies were collected using both traditional manual data entry and the EHR2EDC module. The outcome variable was the percentage of data accurately transferred using the EHR2EDC technology. This percentage was calculated considering all collected data and the data in four domains: demographics (DM), vital signs (VS), laboratories (LB) and concomitant medications (CM). Results Overall, 6143 data points (39.6% of the data in the scope of the TransFAIR study and 16.9% when considering all data) were accurately transferred using the platform. LB data represented 65.4% of the data transferred; VS data, 30.8%; DM data, 0.7% and CM data, 3.1%. Conclusions The objective of accurately transferring at least 15% of the manually entered trial datapoints using the EHR2EDC module was achieved. Collaboration and codesign by hospitals, industry, technology company, supported by the Institute of Innovation through Health Data was a success factor in accomplishing these results. Further work should focus on the harmonisation of data standards and improved interoperability to extend the scope of transferable EHR data.

These CTs will be conducted in a completely usual way, and will not be affected by the TransFAIR study. The data collected in the CSs will serve as a control. They are named "CONTROL Data".
On a top of each CT, the EHR2EDC autocomplete module will be implemented in a separate mirror study to be used as the experimental arm. It will collect the "TransFAIR Data". The data collected in this way will be compared to the CONTROL Data of its sister CT, to evaluate the new tool.

Figure 1; TransFAIR Study
The TransFAIR study is not a clinical trial, it is a technology evaluation study. The data collected in the TransFAIR study must not be used for any regulatory purpose. Only data collected in the traditional clinical trials (Control) are eligible to support regulatory obligations. Patients included in the traditional clinical trials, will be informed that their data, collected in the context of the traditional clinical trials (Control) are expected to be collected in the TransFAIR technology study, after receiving their verbal or written consent.

Figure 2 : Clinical Study vs. TransFAIR study Design Vv
For the purpose of the study, each protocol in in the TransFAIR study will have a specific data base setup in mirror of its Clinical Trial sister, this way nullifying the impact on the CT.

Context
The Center for Drug Evaluation and Research (CDER)  investigations of new drugs, this will be a key infrastructure component of the health learning system approach aiming at using health data to improve provision of care to patients.
The EHR2EDC consortium has developed a generalizable module allowing semi-automatic transfer (under control of the principal investigator and delegated personnel) of patient data and provenance metadata from Electronic Health Records (EHRs) to Electronic Data Capture systems (EDCs), (i.e. eCRFs). The purpose of this study is to evaluate capability of the EHR2EDC module in real life with real patient data via several clinical protocols in different therapeutic areas, conducted at several investigational sites across Europe.

Evaluation plan and methods
This study deals with a technological evaluation, with the objective of semi-automatically* processing a certain number of data usually collected and transcribed manually. The unit of analysis is therefore the data element as entered in an eCRF. The data collected relates to the patients included in the study period transFAIR (or earlier) in one of the trials listed in Table 1 (List of Candidate reference Clinical trials).
The data included in this evaluation are the data for which the EHR2EDC project produced and delivered a mapping catalog to the EHR2EDC pivot model.
The data domains concerned: -Laboratory examinations -Demographics -Vital signs -Procedures, -Diagnostic -Prescriptions (before, during and during hospitalization) -Present and past medical conditions -Other (to be further defined, ex: The control data will firstly be collected and monitored by the sponsor monitors (queries and resolution) in the eCRFs of the reference studies (Control Data). After collection in clinical trial eCRFs. The same data will be collected in the TransFAIR study using the EHR2EDC device. This evaluation will demonstrate the added value of such technology in clinical trials for hospital site staff in terms of the reduction of time and effort for data collection and entry, and an increase of the data quality of the EDC.
*The term "semi-automatic" is equivalent to "automatically transferred under control of Principal Investigator and delegated personnel".

Objectives and end points Objectives Endpoints Primary
To assess the percentage of data that can be processed by EHR2EDC To demonstrate at least 15% of the data usually manually entered into the eCRF can be semiautomatically and accurately transferred into the EDC using EHR2EDC module.

Secondary
To compare EHR2EDC data collection steps and activities versus the manual data entry process at site level

Measure
For each actor the steps and activities will be described and documented for each separate process, to compare the number of steps needed for each process.
To compare EHR2EDC data collection workload versus the manual entry process at the site level For each actor the workload will be documented through surveys (& system/self-reporting) to assess time, effort and usability of each process.
To compare data management activities with or without the EHR2EDC solution the sponsor level For each study the number of queries (data related enquiries) generated will be compared for each process (feasibility to be confirmed) To compare the data accuracy of the EHR2EDC databases versus CTs databases.
Erroneous data in the two database with the same dataset.

Exploratory
To assess the generalizability of the EHR2EDC module Description and characterization of : sponsor and site workload between studies from different sponsor data correctly transferred (percentage of the total data transferred and classification of data by domain) To qualify the data quality of each database by comparing the data queries of both databases Characterization, classification and quantification, of the data manager queries and compare the data queries of both databases BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Two periods must to be distinguished: • Retrospective period: will focus on a transfer of data already collected during the RCTs to be semi-automatically transferred into the mirror database. • Prospective period: data will be collected at least once a week by the PI or delegated personnel.

Candidate List of Studies
The list below, is the studies that meet the eligibility criteria: -Must be conducted at least one of the EHR2EDC partner hospitals. Preference will be given to studies planned at least two of the partner hospitals. -Must have more than 4 patient's visits in the first six months.
-Should collect local laboratory data, demographics, vital signs BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s)  Primary judgment criterion -An estimate of the proportion with its 95% confidence interval will be provided. The exact calculation method will be used if the approximation of the normal law is not possible

Explanatory analyzes
A subgroup analysis is planned on the following variables: •